Genetic Analysis Workshop 14: microsatellite and single-nucleotide polymorphism marker loci for genome-wide scans.
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Databases, Genetic↗
Biomedical subjects
Laura Almasy
Publications and source records attributed to Laura Almasy.
Smoothing of the bivariate LOD score for non-normal quantitative traits.
Variance component analysis provides an efficient method for performing linkage analysis for quantitative traits. However, type I error of variance components-based likelihood ratio testing may be affected when phenotypic data are non-normally distributed (especially with high values of kurtosis). This results in inflated LOD scores when the normality assumption does not hold. Even though different solutions have been proposed to deal with this problem with univariate phenotypes, little work has been done in the multivariate case. We present an empirical approach to adjust the inflated LOD scores obtained from a bivariate phenotype that violates the assumption of normality. Using the Collaborative Study on the Genetics of Alcoholism data available for the Genetic Analysis Workshop 14, we show how bivariate linkage analysis with leptokurtotic traits gives an inflated type I error. We perform a novel correction that achieves acceptable levels of type I error.
Alcoholism↗
A comparison of univariate, bivariate, and trivariate whole-genome linkage screens of genetically correlated electrophysiological endophenotypes.
We used a maximum-likelihood based multipoint linkage approach implemented in SOLAR to examine simultaneously linkage for three electrophysiological endophenotypes from the Collaborative Study of the Genetics of Alcoholism: TTTH1, TTTH2, and TTTH3. These endophenotypes have been identified as markers of alcohol dependence susceptibility. Data were from 905 individuals in 143 families. Measured covariates considered included sex, age at electrophysiology data collection, habitual smoking status, and the maximum number of drinks consumed in a 24-hour period. Comparisons were made among genome-wide univariate, bivariate, and trivariate linkage analyses using genotypes based on microsatellite markers supplied by the Center for Inherited Disease Research, and genotypes based on single-nucleotide polymorphism markers provided by Illumina. All LODs were corrected to a standard equivalent to 1 degree of freedom. Using the trivariate approach and the microsatellite-based genotypes, we estimated a maximum multipoint linkage signal of LOD = 2.66 on chromosome 7q at 157 cM. Analyses using the Illumina SNP genotypes produced similar results, yielding a maximum multipoint LOD of 2.95 on 7q at 174 cM. These regions of interest correspond to those identified in the univariate and bivariate linkage screens. Our results suggest that trivariate multipoint linkage analyses have utility in the further characterization of chromosomal regions potentially containing genes influencing the phenotypes being examined. Based on a comparison of the number of LOD scores achieving statistical significance, our results suggest that the microsatellite- and Illumina SNP-based genotypes have similar utility for detecting genomic regions of interest.
Chromosome Mapping↗
Effect of genotype x alcoholism interaction on linkage analysis of an alcoholism-related quantitative phenotype.
Studies have shown that genetic and environmental factors and their interactions affect several alcoholism phenotypes. Genotype x alcoholism (GxA) interaction refers to the environmental (alcoholic and non-alcoholic) influences on the autosomal genes contributing to variation in an alcoholism-related quantitative phenotype. The purpose of this study was to examine the effects of GxA interaction on the detection of linkage for alcoholism-related phenotypes. We used phenotypic and genotypic data from the Collaborative Study on the Genetics of Alcoholism relating to 1,388 subjects as part of Genetic Analysis Workshop 14 problem 1. We analyzed the MXDRNK phenotype to detect GxA interaction using SOLAR. Upon detecting significant interaction, we conducted variance-component linkage analyses using microsatellite marker data. For maximum number of drinks per a 24 hour period, the highest LODs were observed on chromosomes 1, 4, and 13 without GxA interaction. Interaction analysis yielded four regions on chromosomes 1, 4, 13, and 15. On chromosome 4, a maximum LOD of 1.5 at the same location as the initial analysis was obtained after incorporating GxA interaction effects. However, after correcting for extra parameters, the LOD score was reduced to a corrected LOD of 1.1, which is similar to the LOD observed in the non-interaction analysis. Thus, we see little differences in LOD scores, while some linkage regions showed large differences in the magnitudes of estimated quantitative trait loci heritabilities between the alcoholic and non-alcoholic groups. These potential hints of differences in genetic effect may influence future analyses of variants under these linkage peaks.
Alcoholism↗
X chromosome effects and their interactions with mitochondrial effects.
We report a simple and rapid method for detecting additive genetic variance due to X-linked loci in the absence of marker data for this chromosome. We examined the interaction of this method with an established method for detecting mitochondrial linkage (another source of sex-asymmetric genetic covariance). When applied to data from the Collaborative Study on the Genetics of Alcoholism, this method found evidence of X-chromosomal linkage for one continuous trait (ntth1) and one discrete trait (SPENT). Evidence of mitochondrial contribution was found for one discrete trait (CRAVING) and three continuous traits (ln(CIGPKYR), ecb21, and tth1). Results for ntth1 suggest that methods that do not also allow for male-female heterogeneity in environmental variance may be overly conservative in detection of X-chromosomal effects.
Chromosomes, Human, X↗
Mitochondrial genetic effects on latent class variables associated with susceptibility to alcoholism.
We report the results of statistical genetic analyses of data from the Collaborative Study on the Genetics of Alcoholism prepared for the Genetic Analysis Workshop 14 to detect and characterize maternally inherited mitochondrial genetic effects on variation in latent class psychiatric/behavioral variables employed in the diagnosis of alcoholism. Using published extensions to variance decomposition methods for statistical genetic analysis of continuous and discrete traits we: 1) estimated the proportion of the variance in each trait due to the effects of mitochondrial DNA (mtDNA), 2) tested for pleiotropy, both mitochondrial genetic and residual additive genetic, between trait pairs, and 3) evaluated whether the simultaneous estimation of mitochondrial genetic effects on these traits improves our ability to detect and localize quantitative trait loci (QTL) in the nuclear genome. After correction for multiple testing, we find significant (p < 0.009) mitochondrial genetic contributions to the variance for two latent class variables. Although we do detect significant residual additive genetic correlations between the two traits, there is no evidence of a residual mitochondrial genetic correlation between them. Evidence for autosomal QTL for these traits is improved when linkage screens are conditioned on significant mitochondrial genetic effects. We conclude that mitochondrial genes may contribute to variation in some latent class psychiatric/behavioral variables associated with alcoholism.
Alcoholism↗
A comparison of discrete versus continuous environment in a variance components-based linkage analysis of the COGA data.
BACKGROUND: The information content of a continuous variable exceeds that of its categorical counterpart. The parameterization of a model may diminish the benefit of using a continuous variable. We explored the use of continuous versus discrete environment in variance components based analyses examining gene x environment interaction in the electrophysiological phenotypes from the Collaborative Study on the Genetics of Alcoholism. RESULTS: The parameterization using the continuous environment produced a greater number of significant gene x environment interactions and lower AICs (Akaike's information criterion). In these cases, the genetic variance increased with increasing cigarette pack-years, the continuous environment of interest. This did not, however, result in enhanced LOD scores when linkage analyses incorporated the gene x continuous environment interaction. CONCLUSION: Alternative parameterizations may better represent the functional relationship between the continuous environment and the genetic variance.
Alcoholism↗
Linkage disequilibrium across two different single-nucleotide polymorphism genome scans.
Linkage disequilibrium (LD) content was calculated for the Genetic Analysis Workshop 14 Affymetrix and Illumina single-nucleotide polymorphism (SNP) genome scans of the Collaborative Study on the Genetics of Alcoholism samples. Pair-wise LD was measured as both D' and r2 on 505 pedigree founder individuals. The r2 estimates were then used to correct the multipoint identity by descent matrix (MIBD) calculation to account for LD and LOD scores on chromosomes 3 and 18 were calculated for COGA's ttdt3 electrophysiological trait using those MIBDs. Extensive LD was observed throughout both marker sets, and it was higher in Affymetrix's more dense SNP map. However, SNP density did not solely account for Affymetrix's higher LD. MIBD estimation procedures assume linkage equilibrium to construct genotypes of non-genotyped pedigree founder individuals, and dense SNP genotyping maps are likely to contain moderate to high LD between markers. LOD score plots calculated after correction for LD followed the same general pattern as uncorrected ones. Since in our study almost half of the pedigree founders were genotyped, it is possible that LD had a minor impact on the LOD scores. Caution should probably be taken when using high density SNP maps when many non-genotyped founders are present in the study pedigrees.
Female↗
Endophenotypes successfully lead to gene identification: results from the collaborative study on the genetics of alcoholism.
The use of endophenotypes has been proposed as a strategy to aid gene identification efforts for complex phenotypes [Gottesman, I. I., and Shields J. (1972). Schizophrenia and Genetics: A Twin Study Vantage Point. London: Academic]. As part of the Collaborative Study of the Genetics of Alcoholism (COGA) project, we have analyzed electrophysiological endophenotypes, in addition to clinical diagnoses, as part of our effort to identify genes involved in the predisposition to alcohol dependence. In this paper we summarize published results from linkage and association analyses of two chromosomal regions in which the use of endophenotypes has successfully led to the identification of genes associated with alcohol dependence [GABRA2 (Edenberg et al., (2004). Am. J. Hum. Genet. 74:705-714) and CHRM2 (Wang et al., (2004). Hum. Mol. Genet. 13:1903-1911)]. Our experience in the COGA project has been that the analysis of endophenotypes provides several advantages over diagnostic phenotypes, including the strength and localization of the linkage signal. Our results provide an illustration of the successful use of endophenotypes to identify genes involved in the predisposition to a complex psychiatric phenotype, a strategy originally proposed by Gottesman and Shields in 1972.
Alcoholism↗
Functional variant in a bitter-taste receptor (hTAS2R16) influences risk of alcohol dependence.
A coding single-nucleotide polymorphism (cSNP), K172N, in hTAS2R16, a gene encoding a taste receptor for bitter beta -glucopyranosides, shows significant association with alcohol dependence (P = .00018). This gene is located on chromosome 7q in a region reported elsewhere to exhibit linkage with alcohol dependence. The SNP is located in the putative ligand-binding domain and is associated with an increased sensitivity to many bitter beta -glucopyranosides in the presence of the N172 allele. Individuals with the ancestral allele K172 are at increased risk of alcohol dependence, regardless of ethnicity. However, this risk allele is uncommon in European Americans (minor-allele frequency [MAF] 0.6%), whereas 45% of African Americans carry the allele (MAF 26%), which makes it a much more significant risk factor in the African American population.
Black or African American↗
Human F7 sequence is split into three deep clades that are related to FVII plasma levels.
It is widely accepted that FVII levels are strongly, consistently, and independently related to cardiovascular risk. These levels are influenced by genetic and environmental factors. Among the genetic factors, only a limited number of polymorphisms in the F7 gene have been reported, and they explain only a small proportion of the genetic variability. Recently, we have accomplished the complete dissection of the F7 quantitative trait locus responsible for all of the genetic variability observed in FVII levels. Now, we present the thorough study of the haplotype organization of F7 DNA sequence variation among individuals and the evolutionary processes that produced this variation, by sequencing 15 kb of genomic DNA sequence from the F7 locus in 40 unrelated individual (80 chromosomes) from the genetic analysis of idiopathic thrombophilia (GAIT) project as well as four non-human primate species. Our study revealed 49 polymorphisms, of which 39 SNPs were further considered. Genotyping of these DNA variations in the whole family-based GAIT sample helped resolve linkage phases, and a total of 37 distinct haplotypes were identified.Tajima's D was significantly positive in this sample, suggesting balancing selection. This parameter was a reflection of the phylogenetic structure of F7 haplotype, which was deeply split into three well-supported clades or haplogroups, suggesting that functional differences among F7 variants do not depend on a few single-site variations. Moreover, haplogroup 2 was associated with high FVII levels and haplogroup 3 with low levels. In this study, we have for the first time established a clear relation between genotypic variability structure and phenotypic variability of a particular quantitative trait involved in a complex disease.
Animals↗
Evidence of genetic overlap of schizophrenia and bipolar disorder: linkage disequilibrium analysis of chromosome 18 in the Costa Rican population.
The long-standing concept that schizophrenia (SC) and bipolar disorder (BP) represent two distinct illnesses has been recently challenged by findings of overlap of genetic susceptibility loci for these two diseases. We report here the results of a linkage disequilibrium (LD) analysis of chromosome 18 utilizing subjects with SC from the Central Valley of Costa Rica. Evidence of association (P < 0.05) was obtained in three chromosomal regions: 18p11.31 (D18S63), 18q12.3 (D18S474), and 18q22.3-qter (D18S1161, D18S70), all of which overlap or are in close proximity with loci previously shown to be in LD with BP, type I in this population. Since both the SC and bipolar samples contained cases with a history of mania and almost all cases of SC and BP had a history of psychosis, we performed an alternative phenotyping strategy to determine whether presence or absence of mania, in the context of psychosis, would yield distinct linkage patterns along chromosome 18. To address this issue, a cohort of psychotic patients (including a range of DSMIV diagnoses) was divided into two groups based on the presence or absence of mania. Regions that showed association with SC showed segregation of association when the sample was stratified by history of mania. Our results are compared with previous genetic studies of susceptibility to SC or BP, in Costa Rica as well as in other populations. This study illustrates the importance of detailed phenotype analysis in the search for susceptibility genes influencing complex psychiatric disorders in isolated populations and suggests that subdivision of psychoses by presence or absence of past mania syndromes may be useful to define genetic subtypes of chronic psychotic illness.
Bipolar Disorder↗
Genomewide linkage analysis of soluble transferrin receptor plasma levels.
Genetic control of soluble transferrin receptor (sTfR) levels was demonstrated using family-based studies (GAIT, Genetic Analysis of Idiopathic Thrombophilia project); moreover, a genetic relationship was observed between sTfR and the risk for thrombosis, suggesting that these phenotypes shared genetic determinants. We studied the regions that control sTfR. To assess such regions, a full genome scan was carried out using 604 highly polymorphic deoxyribonucleic acid markers (resolution 7.3 cM) in 21 extended pedigrees (358 individuals). Then, a quantitative trait linkage analysis was performed using variance components methods. The genomewide scan linkage analysis showed two regions (quantitative trait locus or QTL) with significant limit of detection (LOD) scores (2q23.14, LOD score = 2.64, nominal p = 0.00024; 3q21.2, LOD score = 1.94, nominal p = 0.0014). There were no obvious candidate genes in these regions. In conclusion, this linkage analysis suggested the existence of a QTL in 2q23.14 that probably harbored a gene (or genes) controlling sTfR levels. Moreover, a second linkage signal was observed in 3q21.2; albeit the evidence for this second locus was lower. The next step will be to identify the gene(s) and its possible involvement in thrombosis and iron homeostasis.
Chromosome Mapping↗
A genomewide exploration suggests a new candidate gene at chromosome 11q23 as the major determinant of plasma homocysteine levels: results from the GAIT project.
Homocysteine (Hcy) plasma level is an independent risk marker for venous thrombosis, myocardial infarction, stroke, congestive heart failure, osteoporotic fractures, and Alzheimer disease. Hcy levels are determined by the interaction of genetic and environmental factors. The genetic basis is still poorly understood, since only the MTHFR 677 C-->T polymorphism has been consistently associated with plasma Hcy levels. We conducted a genomewide linkage scan for genes affecting variation in plasma Hcy levels in 398 subjects from 21 extended Spanish families. A variance-components linkage method was used to analyze the data. The strongest linkage signal (LOD score of 3.01; genomewide P = .035) was found on chromosome 11q23, near marker D11S908, where a candidate gene involved in the metabolism of Hcy (the nicotinamide N-methyltransferase gene [NNMT]) is mapped. Haplotype analyses of 10 single-nucleotide polymorphisms within this gene found one haplotype associated with plasma Hcy levels (P = .0003). Our results, to our knowledge, represent the first genomic scan for quantitative variation in Hcy plasma levels. They strongly suggest that the NNMT gene could be a major genetic determinant of plasma Hcy levels in Spanish families. Since this gene encodes an enzyme involved in Hcy synthesis, this finding would be consistent with known biochemical pathways. These data could be relevant in determining the relationships between Hcy level, cardiovascular disease, osteoporosis, and Alzheimer disease.
Chromosome Mapping↗
A genome search for genetic determinants that influence plasma fibrinogen levels.
BACKGROUND: Fibrinogen levels are a widely accepted risk factor for cardiovascular disease, but the extent of the genetic component is unknown. MATERIALS AND RESULTS: To search for these genes, we conducted a genome-wide scan using 21 Spanish families from the Genetic Analysis of Idiopathic Thrombophila (GAIT) Project. Two loci were detected: 1 on chromosome 12 and another on chromosome 14. There are no cardiovascular-related candidate genes on chromosome 14, which implies that this locus represents a novel cardiovascular risk factor. Importantly, the locus on chromosome 12 contains the hepatocyte nuclear factors (TCF1), a candidate gene involved in the hepatocyte-specific transcription of the fibrinogen alpha-chain and beta-chain genes. Three polymorphisms in TCF1 showed significant association with fibrinogen levels, supporting the implication of TCF1 in the determination of this phenotype. CONCLUSIONS: Two loci, 1 on chromosome 12 (most likely the TCF1) and another on chromosome 14, are important determinants of fibrinogen levels in Spanish families. These data should help define the relationship between fibrinogen levels and the risk of cardiovascular disease.
Adolescent↗
Linkage of the cholesterol 7alpha-hydroxylase gene and low-density lipoprotein cholesterol conditional on apolipoprotein E association: the National Heart, Lung, and Blood Institute Family Heart Study.
BACKGROUND: Genetic factors account for approximately 50% of the individual variation in plasma low-density lipoprotein cholesterol (LDL-C) concentrations in the general population. Several candidate genes have been proposed but their relative contributions to the variance in LDL-C are not known, except for apolipoprotein E (apoE). We report here an investigation of the relationship between LDL-C and cholesterol 7alpha-hydroxylase (CYP7), as well as apoE and low-density lipoprotein receptor (LDLR), three pivotal genes in LDL metabolism. METHODS: Our study population included more than 200 nuclear families with increased coronary heart disease (CHD) risk from the National Heart, Lung, and Blood Institute (NHLBI) Family Heart Study. Variance-component linkage methods, a measured genotype approach, and a variance-component linkage analysis conditional on a measured genotype association were used. RESULTS: The results showed significant linkage between a genetic determinant of plasma LDL-C concentrations and a polymorphism near CYP7 with its allelic variation accounting for 27% of the total LDL-C variation. There is significant association between plasma LDL-C concentrations and apoE genotypes. Conditional on the apoE association, the total LDL-C variation accounted by allelic variation of a polymorphism near CYP7 was increased significantly. CONCLUSION: Our results suggest the apoE and CYP7 may be two important genes accounting for the genetic variation of plasma LDL-C concentrations in a population with cardiovascular diseases.
Adult↗
Linkage analysis of factors underlying insulin resistance: Strong Heart Family Study.
In previous work in non-diabetic participants of the Strong Heart Family Study, we identified three heritable principal components of nine insulin resistance (IR) phenotypes: 1) a glucose/insulin/obesity factor, 2) a blood pressure factor, and 3) a dyslipidemia factor. To localize quantitative trait loci (QTL) potentially influencing these factors, we conducted a genome scan of factor scores in Strong Heart Family Study participants. Approximately 599 men and women, >or=18 years of age, in 32 extended families at three centers (in Arizona, Oklahoma, and North and South Dakota), were examined between 1997 and 1999. We used variance components linkage analysis to identify QTLs for the IR factors. With age, sex, and study center as covariates, we detected linkage of the glucose/insulin/obesity factor to chromosome 4 (robust logarithm of the odds (LOD) = 2.2), the dyslipidemia factor to chromosome 12 (robust LOD = 2.7), and the blood pressure factor to chromosome 1 (robust LOD = 1.6). The peak linkage signals identified for these IR factors support several positive findings from other studies and occur in regions harboring interesting candidate genes. The corroboration of existing QTLs will bring us closer to the identification of the functional genes that predispose to IR.
Aged↗
Common genetic and environmental effects on lipid phenotypes: the HERITAGE family study.
OBJECTIVE: Despite the well known genetic component influencing plasma lipid-lipoprotein levels and the observed correlations among these traits, little is known about pleiotropic heritable determinants among them. Our aim is to investigate pair-wise polygenic and environmental correlations among lipid-lipoprotein levels at baseline and in response to regular exercise in Whites and Blacks. METHODS: Common pair-wise genetic and environmental correlations among levels of total cholesterol (TC), LDL-C, ApoB, HDL-C (also HDL2-C and HDL3-C), triglycerides (TG, HDL-TG and LDL-TG) and ApoA-1 were investigated at baseline and again after a 20-week endurance exercise program using a variance-components-decomposition. RESULTS: With a few exceptions, all lipid phenotypes were heritable at baseline and for training responses in Blacks and Whites. Strong to high genetic and environmental correlations (0.4 < rho(g) < 0.7) were observed for the majority of the baseline pair-wise traits. For training responses, many of the same patterns were noted, although fewer genetic correlations were significant as compared to the baseline results. CONCLUSIONS: Results suggest that the observed phenotypic correlations among many of these traits may be due to in part to pleiotropic genes, in particular between LDL-C and ApoB and between TG and HDL-C. This shared genetic architecture should be considered in follow-up gene finding studies.
Adult↗